Jaeha Kung

Orcid: 0000-0001-6151-8602

According to our database1, Jaeha Kung authored at least 48 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
One-Spike SNN: Single-Spike Phase Coding with Base Manipulation for ANN-to-SNN Conversion Loss Minimization.
CoRR, 2024

Skipformer: Evolving Beyond Blocks for Extensively Searching On-Device Language Models With Learnable Attention Window.
IEEE Access, 2024

A Ready-to-Use RTL Generator for Systolic Tensor Arrays and Analysis Using Open-Source EDA Tools.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2024

A Full SW-HW Demonstration of GEMM Accelerators with RISC-V Instruction Extensions.
Proceedings of the International Conference on Electronics, Information, and Communication, 2024

OPAL: Outlier-Preserved Microscaling Quantization Accelerator for Generative Large Language Models.
Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

A 3.3-to-11V-Supply-Range 10μW/Ch Arbitrary-Waveform-Capable Neural Stimulator with Output-Adaptive-Self-Bias and Supply-Tracking Schemes in 0.18μm Standard CMOS.
Proceedings of the IEEE Custom Integrated Circuits Conference, 2024

NDPipe: Exploiting Near-data Processing for Scalable Inference and Continuous Training in Photo Storage.
Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

2023
FlexBlock: A Flexible DNN Training Accelerator With Multi-Mode Block Floating Point Support.
IEEE Trans. Computers, September, 2023

Simplified Compressor and Encoder Designs for Low-Cost Approximate Radix-4 Booth Multiplier.
IEEE Trans. Circuits Syst. II Express Briefs, March, 2023

All-rounder: A flexible DNN accelerator with diverse data format support.
CoRR, 2023

Improving Hardware Efficiency of a Sparse Training Accelerator by Restructuring a Reduction Network.
Proceedings of the 21st IEEE Interregional NEWCAS Conference, 2023

A 1V 136.6dB-DR 4kHz-BW $\Delta\Sigma$ Current-to-Digital Converter with a Truncation-Noise-Shaped Baseline-Servo-Loop in 0.18\mu\mathrm{m}$ CMOS.
Proceedings of the IEEE International Solid- State Circuits Conference, 2023

DBPS: Dynamic Block Size and Precision Scaling for Efficient DNN Training Supported by RISC-V ISA Extensions.
Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

2022
Implication of Optimizing NPU Dataflows on Neural Architecture Search for Mobile Devices.
ACM Trans. Design Autom. Electr. Syst., 2022

AutoRelax: HW-SW Co-Optimization for Efficient SpGEMM Operations With Automated Relaxation in Deep Learning.
IEEE Trans. Emerg. Top. Comput., 2022

A 46-nF/10-MΩ Range 114-aF/0.37-Ω Resolution Parasitic- and Temperature-Insensitive Reconfigurable RC-to-Digital Converter in 0.18-μm CMOS.
IEEE Trans. Circuits Syst. I Regul. Pap., 2022

SEMS: Scalable Embedding Memory System for Accelerating Embedding-Based DNNs.
IEEE Comput. Archit. Lett., 2022

LightNorm: Area and Energy-Efficient Batch Normalization Hardware for On-Device DNN Training.
Proceedings of the IEEE 40th International Conference on Computer Design, 2022

DualPIM: A Dual-Precision and Low-Power CNN Inference Engine Using SRAM- and eDRAM-based Processing-in-Memory Arrays.
Proceedings of the 4th IEEE International Conference on Artificial Intelligence Circuits and Systems, 2022

2021
High-throughput Near-Memory Processing on CNNs with 3D HBM-like Memory.
ACM Trans. Design Autom. Electr. Syst., 2021

Design and Analysis of Approximate Compressors for Balanced Error Accumulation in MAC Operator.
IEEE Trans. Circuits Syst. I Regul. Pap., 2021

Deep Partitioned Training From Near-Storage Computing to DNN Accelerators.
IEEE Comput. Archit. Lett., 2021

Adaptive Input-to-Neuron Interlink Development in Training of Spike-Based Liquid State Machines.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2021

ZeBRA: Precisely Destroying Neural Networks with Zero-Data Based Repeated Bit Flip Attack.
Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020
Balancing Computation Loads and Optimizing Input Vector Loading in LSTM Accelerators.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2020

Towards Scalable Analytics with Inference-Enabled Solid-State Drives.
IEEE Comput. Archit. Lett., 2020

Defending Against Flush+Reload Attack With DRAM Cache by Bypassing Shared SRAM Cache.
IEEE Access, 2020

2019
Noise Tolerance of an Energy-Scalable Deep Learning Model with Two Extreme Bit-Precisions.
Proceedings of the 2019 International SoC Design Conference, 2019

WMixNet: An Energy-Scalable and Computationally Lightweight Deep Learning Accelerator.
Proceedings of the 2019 IEEE/ACM International Symposium on Low Power Electronics and Design, 2019

Similarity-Based LSTM Architecture for Energy-Efficient Edge-Level Speech Recognition.
Proceedings of the 2019 IEEE/ACM International Symposium on Low Power Electronics and Design, 2019

Peregrine: A Flexible Hardware Accelerator for LSTM with Limited Synaptic Connection Patterns.
Proceedings of the 56th Annual Design Automation Conference 2019, 2019

2018
Efficient Object Detection Using Embedded Binarized Neural Networks.
J. Signal Process. Syst., 2018

Adaptive Precision Cellular Nonlinear Network.
IEEE Trans. Very Large Scale Integr. Syst., 2018

Maximizing system performance by balancing computation loads in LSTM accelerators.
Proceedings of the 2018 Design, Automation & Test in Europe Conference & Exhibition, 2018

The CAMEL approach to stacked sensor smart cameras.
Proceedings of the 2018 Design, Automation & Test in Europe Conference & Exhibition, 2018

2017
Energy-efficient digital hardware platform for learning complex systems.
PhD thesis, 2017

A Power-Aware Digital Multilayer Perceptron Accelerator with On-Chip Training Based on Approximate Computing.
IEEE Trans. Emerg. Top. Comput., 2017

Energy-efficient neural image processing for Internet-of-Things edge devices.
Proceedings of the IEEE 60th International Midwest Symposium on Circuits and Systems, 2017

A Programmable Hardware Accelerator for Simulating Dynamical Systems.
Proceedings of the 44th Annual International Symposium on Computer Architecture, 2017

On-chip training of recurrent neural networks with limited numerical precision.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Adaptive weight compression for memory-efficient neural networks.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2017

2016
Dynamic Approximation with Feedback Control for Energy-Efficient Recurrent Neural Network Hardware.
Proceedings of the 2016 International Symposium on Low Power Electronics and Design, 2016

Neurocube: A Programmable Digital Neuromorphic Architecture with High-Density 3D Memory.
Proceedings of the 43rd ACM/IEEE Annual International Symposium on Computer Architecture, 2016

ReRAM Crossbar based Recurrent Neural Network for human activity detection.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

2015
On the Impact of Energy-Accuracy Tradeoff in a Digital Cellular Neural Network for Image Processing.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2015

A power-aware digital feedforward neural network platform with backpropagation driven approximate synapses.
Proceedings of the IEEE/ACM International Symposium on Low Power Electronics and Design, 2015

2011
Compact thermal models: Assessment and pitfalls.
Proceedings of the International SoC Design Conference, 2011

Thermal signature: a simple yet accurate thermal index for floorplan optimization.
Proceedings of the 48th Design Automation Conference, 2011


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